An Innovative Framework for Lightning Leader Prediction and Protection of Heritage Mangrove Forests Using Cellular Automata

Lightning strikes have been identified to be a major influence for forest fires in addition to causing significant damages to rare fauna. Hence, with the growing concerns related to climate changes, protection of such rare breeds of heritage trees and fauna has become essential. Though international standards have clearly delineated the methodology of lightning protection of trees from lightning strikes, practical aspects related to difficulties related to monitoring, complexities associated with identification of accurate location of lightning protection system (LPS), variations in terrain of the trees, limitations related to the protective zone offered by lightning rod from the context of dense trees etc., continue to present considerable challenges. Research studies have indicated that lightning strikes have led to substantial damages in mangrove forests culminating in disturbances in the forest ecology such as canopy gaps, loss of rare herbs, fauna etc. This research attempts a unique strategy of utilizing 2-dimensional Cellular Automata (2-DCA) based on stochastic field fluctuation criterion (FFC) for leader growth for prediction of lightning leader in a group of mangrove trees in a forest. A random variable which relates to variations associated with atmospheric ionization, air density, etc., is utilized in modelling. Detailed simulations based on case studies have been carried out for varying positions of cloud and the vulnerable locations of lightning strikes are ascertained. Further, the role of lightning strikes at the fringe of rivers (waterways) is analyzed and appropriate methodology for location of lightning rods is also deliberated.